Senior Data Engineer

Tillster

. Own and maintain data warehouse infrastructure across Redshift, BigQuery, and Snowflake .

Posted 9/16/2026full-timeMexico City • MexicoSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data warehouse infrastructure management across Redshift, BigQuery, and Snowflake, with strong capabilities in building and maintaining data pipelines using Python and SQL. Proficient in supporting BI tools like Looker and implementing data quality checks to ensure reliable data-driven decision-making.

Highest-signal resume keywords

Python DevelopmentSQL ProficiencyData Warehouse ManagementAirflow OrchestrationLooker Support

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonSQLRedshiftBigQuerySnowflakeAirflowDbtLookerData Pipeline DevelopmentReal-Time Data Ingestion

Tools & Technologies

AWSBrazeAcousticMoEngageSegmentLookMLGoogle AnalyticsFivetranStitchKinesis

Industry Keywords

Data WarehouseData QualityAgile DevelopmentBusiness IntelligenceData Modeling

Tech Stack

Tools & technologies

AirflowAmazon RedshiftAWSBigQueryCloudJenkinsPythonSQLTableau

About the role

Key responsibilities & impact

Own and maintain data warehouse infrastructure across Redshift, BigQuery, and Snowflake
Build and maintain real-time, batch, and streaming data pipelines
Enable data-driven decisions across marketing, product, engineering, sales/account management, finance, and operations
Design data structures for real-time and near-real-time decision-making
Support the MarTech stack, including Braze, Acoustic, MoEngage, and Segment
Modify and maintain SQL and Python ELT processes loading data into Redshift and other warehouses
Troubleshoot and maintain Airflow/Jenkins orchestration jobs
Collaborate with DevOps and cloud management on underlying infrastructure
Fulfill ad-hoc data extract requests
Provide ad-hoc SQL and analysis support to business stakeholders
Maintain and update Looker Explores and dashboards
Partner with Data Analysts on reporting requirements and efficient pipelines and derived tables
Develop, test, and maintain dbt models
Unify GA4, CRM, and other data sources into a consolidated warehouse structure
Build reusable data models for marketing funnels, segmentation, and campaign analytics
Implement automated data quality checks and validation rules
Document data models and business logic

Requirements

What you’ll need

4+ years of experience developing in Python
4+ years of experience in SQL, including Redshift, Snowflake, and BigQuery
2+ years working on AWS or an equivalent cloud platform
2+ years working with Airflow or comparable orchestration tools
Working knowledge of dbt for data transformation and modeling
Hands-on experience supporting BI tools such as Looker or Tableau
Experience with real-time ingestion tools such as Snowpipe, Stitch, Fivetran, or Kinesis
Experience working in an Agile development environment
No visa sponsorship
Nice to have: experience with Segment, Braze, Acoustic, or MoEngage data integrations
Nice to have: familiarity with LookML and Looker semantic layer concepts
Nice to have: experience with Google Analytics (GA4) as a data source
Nice to have: knowledge of data quality frameworks and CI/CD for data pipelines
Nice to have: exposure to statistics, experimentation (A/B testing), or basic ML concepts

Benefits

Comp & perks

Opportunity to work with innovative technology and talented global teams
Opportunity to help shape the future of intelligent customer experiences
Opportunity to contribute to an AI Native enterprise
Growth-phase, venture-funded company environment
Opportunity to make an impact and gain knowledge from colleagues at all levels
Inclusive and diverse work environment
Equal opportunity employer